ParadisEO-MO: from fitness landscape analysis to efficient local search algorithms

被引：0
作者：
J. Humeau
A. Liefooghe
E. -G. Talbi
S. Verel
机构：
[1] École des Mines de Douai,Département IA
[2] DOLPHIN Research Team,Inria Lille
[3] Université Lille 1,Nord Europe
[4] Université Nice Sophia Antipolis,Laboratoire LIFL, UMR CNRS 8022
来源：
Journal of Heuristics | 2013年 / 19卷
关键词：
Local search; Metaheuristic; Fitness landscapes ; Conceptual unified model; Algorithm design and analysis; Software framework ;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a general-purpose software framework dedicated to the design, the analysis and the implementation of local search metaheuristics: ParadisEO-MO. A substantial number of single solution-based local search metaheuristics has been proposed so far, and an attempt of unifying existing approaches is here presented. Based on a fine-grained decomposition, a conceptual model is proposed and is validated by regarding a number of state-of-the-art methodologies as simple variants of the same structure. This model is then incorporated into the ParadisEO-MO software framework. This framework has proven its efficiency and high flexibility by enabling the resolution of many academic and real-world optimization problems from science and industry.
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页码：881 / 915
页数：34
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